Abstract: Decode and forward buffer aided relay selection and transmission power allocation systems and method are provided for cognitive radio network that is equipped with multiple-input-multiple-output (MIMO). A low complexity MIMO-based relay selection scheme that maximizes the single-hop normalized sum rate of the primary network (PN) and secondary network (SN) is proposed including a sub-optimal antenna transmission power allocation scheme that maximizes the single-hop normalized sum rate of the PN and the SN is proposed. For power optimization, first, optimal expressions for the transmission power per antenna of both the PN and SN nodes are derived separately. The derived expressions are then used in an iterative algorithm to produce a near-optimum solution that maximizes the normalized sum rate per time slot.

Abstract: Decode and forward buffer aided relay selection and transmission power allocation systems and method are provided for cognitive radio network that is equipped with multiple-input-multiple-output (MIMO). A low complexity MIMO-based relay selection scheme that maximizes the single-hop normalized sum rate of the primary network (PN) and secondary network (SN) is proposed including a sub-optimal antenna transmission power allocation scheme that maximizes the single-hop normalized sum rate of the PN and the SN is proposed. For power optimization, first, optimal expressions for the transmission power per antenna of both the PN and SN nodes are derived separately. The derived expressions are then used in an iterative algorithm to produce a near-optimum solution that maximizes the normalized sum rate per time slot.

Abstract: Decode and forward buffer aided relay selection and transmission power allocation systems and method are provided for cognitive radio network that is equipped with multiple-input-multiple-output (MIMO). A low complexity MIMO-based relay selection scheme that maximizes the single-hop normalized sum rate of the primary network (PN) and secondary network (SN) is proposed including a sub-optimal antenna transmission power allocation scheme that maximizes the single-hop normalized sum rate of the PN and the SN is proposed. For power optimization, first, optimal expressions for the transmission power per antenna of both the PN and SN nodes are derived separately. The derived expressions are then used in an iterative algorithm to produce a near-optimum solution that maximizes the normalized sum rate per time slot.

Abstract: Decode and forward buffer aided relay selection and transmission power allocation systems and method are provided for cognitive radio network that is equipped with multiple-input-multiple-output (MIMO). A low complexity MIMO-based relay selection scheme that maximizes the single-hop normalized sum rate of the primary network (PN) and secondary network (SN) is proposed including a sub-optimal antenna transmission power allocation scheme that maximizes the single-hop normalized sum rate of the PN and the SN is proposed. For power optimization, first, optimal expressions for the transmission power per antenna of both the PN and SN nodes are derived separately. The derived expressions are then used in an iterative algorithm to produce a near-optimum solution that maximizes the normalized sum rate per time slot.

Abstract: The spectrum-efficient secondary users grouping method for two-tier cognitive radio groups femtocell base stations (FBSs) and macrocell secondary users (MSUs) into non-interfering groups based on their GPS location information, and then serves the FBSs/MSUs within each group using the same channel. A first approach for grouping the secondary users (SUs) is distance-based. A second approach utilizes profit maximization. Both approaches are extended to a co-channel deployment scenario where the FBSs can share part of the channels purchased for the MSUs to further reduce the number of channels to be purchased from the PU networks. The distance-based grouping method finds the minimum number of groups such that the desired quality of service (QoS) determined by an outage probability threshold is maintained. The profit maximization method tries to find the set of SUs that maximizes the expected total profit of the SU network.

Abstract: The primary channel selection method for relay networks functions in a relaying cognitive network where a number of relays are used to forward the source message to destination. The primary users utilize orthogonal spectrum bands. One primary user is selected among the available primary users in order to share its spectrum with the secondary users (source and relay). A certain amount of interference is allowed between the primary and secondary users when the primary users' channels are shared by the secondary users.

Abstract: The bandwidth efficient cooperative two-way amplify-and-forward relaying method allows users in a secondary network to utilize a relay node in the primary users' network while minimizing co-channel interference. In the method, two primary user network sources communicate through a primary user network relay node. A secondary user network source and a secondary user destination agree to act as relays for the primary network sources, all of the above using amplify-and-forward protocol. In return, the primary network relay node allows the secondary user source to communicate through the primary network relay node with the secondary user destination using decode-and-forward protocol. Five symbols, including four primary user symbols and one secondary user symbol, are transmitted in four time slots for a bandwidth efficiency of 1.25. The primary network relay and the secondary users relay transmissions have their power allocated to minimize symbol error rate and maximize sum rate.

Abstract: The primary channel selection method for relay networks functions in a relaying cognitive network where a number of relays are used to forward the source message to destination. The primary users utilize orthogonal spectrum bands. One primary user is selected among the available primary users in order to share its spectrum with the secondary users (source and relay). A certain amount of interference is allowed between the primary and secondary users when the primary users' channels are shared by the secondary users.

Abstract: The spectrum-efficient secondary users grouping method for two-tier cognitive radio groups femtocell base stations (FBSs) and macrocell secondary users (MSUs) into non-interfering groups based on their GPS location information, and then serves the FBSs/MSUs within each group using the same channel. A first approach for grouping the secondary users (SUs) is distance-based. A second approach utilizes profit maximization. Both approaches are extended to a co-channel deployment scenario where the FBSs can share part of the channels purchased for the MSUs to further reduce the number of channels to be purchased from the PU networks. The distance-based grouping method finds the minimum number of groups such that the desired quality of service (QoS) determined by an outage probability threshold is maintained. The profit maximization method tries to find the set of SUs that maximizes the expected total profit of the SU network.

Abstract: The amplify and forward relay method enhances QOS in wireless networks and is based on the switch-and-examine (SEC) and SEC post-selection (SECps) diversity combining techniques where only a single relay out of multiple relays is used to forward the source signal to the destination. The selection process is performed based on a predetermined switching threshold. Maximal-ratio combining (MRC) is used at the destination to combine the signal on the relay path with that on the direct link.

Abstract: A method of mitigating an interference and reducing costs resulting from a co-existence of a plurality of femtocells and a plurality of macrocells. The method groups the femtocells into groups of non-interferers based on the distances between a plurality of femtocell base stations and a cognitive radio network base station, wherein the distances are calculated based on the locations of a plurality of grouped femtocell base stations. The method accrues a revenue of the profit of the cognitive radio network base station from a plurality of K femto base stations and a plurality of I macro secondary user subscribers while paying only for a plurality of S non-interfering groups of the plurality of femto base stations plus the I macro secondary user subscriber channels.

Abstract: The two-path amplify-and-forward relaying method for bandwidth efficient cognitive radios utilizes a primary user (PU) transmitter cooperating with a secondary user (SU) transmitter and receiver to relay PU data to the PU receiver. The present algorithm makes use of the inter-relay interference (IRI) between the two relay nodes to transmit SU data and cancel this IRI at the PU receiver node. The SU transmission power and the relaying amplifying factors are optimized to minimize the probability of error. Lagrangian multiplier method is used to obtain the optimal solution for the problem. Simulation results show that the present algorithm outperforms the single data transmission and gets closer to the performance of multiple input multiple output (MIMO) system of diversity 3 for PU network and 2 for SU network when a maximum likelihood decoder (MLD) is used.

Abstract: The amplify and forward relay method enhances QOS in wireless networks and is based on the switch-and-examine (SEC) and SEC post-selection (SECps) diversity combining techniques where only a single relay out of multiple relays is used to forward the source signal to the destination. The selection process is performed based on a predetermined switching threshold. Maximal-ratio combining (MRC) is used at the destination to combine the signal on the relay path with that on the direct link.

Abstract: The multi-configuration adaptive layered steered space-time coded (LSSTC) wireless transmission system utilizes Layered Steered Space-Time Codes (LSSTC), a recently proposed multiple-input multiple-output (MIMO) system that combines the benefits of the vertical Bell Labs space-time (V-BLAST) scheme, space-time block codes (STBC) and beamforming. A multi-configuration transmission scheme based on LSSTC and V-BLAST systems uses threshold-based decision making to change the modulation type and the MIMO transmission scheme in order to optimize error performance.

Abstract: The optimal power allocation method for an LSSTC wireless transmission system utilizes Layered Steered Space-Time Codes (LSSTC), a recently proposed multiple-input multiple-output (MIMO) system that combines the benefits of vertical Bell Labs space-time (V-BLAST) scheme, space-time block codes (STBC), and beamforming. A new downlink scheme employs LSSTC with optimal power allocation based on the assumption that the user feeds the base station (BS) with the average signal-to-noise ratio (SNR) per V-BLAST layer through the uplink feedback channel. Such a system enhances the error performance by assigning power to the layers in an optimum manner.

Abstract: The optimal power allocation method for an LSSTC wireless transmission system utilizes Layered Steered Space-Time Codes (LSSTC), a recently proposed multiple-input multiple-output (MIMO) system that combines the benefits of vertical Bell Labs space-time (V-BLAST) scheme, space-time block codes (STBC), and beamforming. A new downlink scheme employs LSSTC with optimal power allocation based on the assumption that the user feeds the base station (BS) with the average signal-to-noise ratio (SNR) per V-BLAST layer through the uplink feedback channel. Such a system enhances the error performance by assigning power to the layers in an optimum manner.

Abstract: The multi-configuration adaptive layered steered space-time coded (LSSTC) wireless transmission system utilizes Layered Steered Space-Time Codes (LSSTC), a recently proposed multiple-input multiple-output (MIMO) system that combines the benefits of the vertical Bell Labs space-time (V-BLAST) scheme, space-time block codes (STBC) and beamforming. A multi-configuration transmission scheme based on LSSTC and V-BLAST systems uses threshold-based decision making to change the modulation type and the MIMO transmission scheme in order to optimize error performance.